Interstitial Lung Diseases (ILD) effects the lung intestitium part will leads to breathing problems and gradually leads to death. A deep learning technique convolutional neural network have been proposed to aid computer aided diagnosis system which enhances the accuracy of diagnosis of ILDs by physician because automatic tissue characterization is a crucial component of CAD system. Deep Convolutional Neural Network (CNN) concept raise the accuracy of medical image analysis for the lung pattern classification.CNN designed for the interstitial lung diseases, consist of five convolutional layers with 2×2 kernels and LeakyReLU activation functions. The CNN use the Adaptive moment estimation optimizer algorithm as a weight updation mechanism in back propagation a process. Experimental results prove superior performance and efficiency of the proposed approach through the comparative analysis of CNN against previous methods.

Convolutional Neural Network, Computer Aided Diagnosis, Interstitial Lung Diseases, Texture classification.

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